GPT-IMGSame credit table, five months apart. The prompt box below has both models in it, so you can run one brief through each and judge the difference on your own work rather than ours.
Both models share one credit table here, so the choice is quality, not budget. What changed between the two OpenAI generations, tested on the same prompts.
If neither OpenAI model fits the brief, these are the ones people move to next for the same kinds of job.
OpenAI latest image model. Sharper instruction following, cleaner in-image text, up to 4K.
Most capable OpenAI model. Supports all quality tiers and up to 4K.
Google latest image model. Sharper edits, cleaner in-image text, steadier subject consistency, up to 4K.
Highest quality Google model. Supports up to 4K resolution.
Strong typography and poster layouts. Handles dense in-image text at 1K and 2K.
Photorealistic detail with tight prompt control. Accepts up to 8 reference images.
Fast and opinionated. Good for posters, memes, and stylized concept art.
Edit an existing image by describing the change. Requires a reference image.
The cheapest way to explore an idea. Sub-second generation at 5 credits per image.
Speed-optimized Krea 2 with a wide stylistic range. Good for stylized ideation and typography-led art.
OpenAI released GPT Image 2.5 on September 8, 2026, five months after GPT Image 2, and framed it as an update rather than a generational leap. Here is what that meant on our prompts, and where the evidence runs out.
A brief stacking six constraints — subject, handle orientation, light direction, background tone, a reserved empty area, and a no-text rule — came back with all six intact on the first run of GPT Image 2.5.
Six labelled regions in one infographic came back spelled correctly, along with six captions the model wrote unprompted. That is the shape of brief that historically returned missing letters.
Swapping a background left the subject, the angle, the highlights, and the framing untouched. Holding the crop is the part most models get wrong.
OpenAI puts generation latency up to 50% below GPT Image 2. When you are iterating a prompt ten times, that is the change you feel most.
Both models share one credit table on GPT-IMG: 10 credits for a 1K Standard draft, 120 for a 4K High render, 15 to 130 for reference edits. Pick on output, not on price.
Each result above is a single generation, not an average of fifty, and our review only covered single-round edits on fresh images. Long edit chains are an open question. Run your own brief on both models before you commit a workflow.
The credit cost is identical, so there is no budget argument for the older model — but three cases survive. If half your catalogue was rendered on GPT Image 2, its look is your house style now. When a brief keeps coming back subtly wrong, a different model is a faster diagnostic than a tenth prompt rewrite. And on photorealistic materials it remains solid enough to be worth a parallel run rather than an automatic skip.
The long version, and the two model pages themselves.
Upgrade for larger monthly credits, faster generation, and commercial-ready output.
Buy credits once and use them whenever you need. Purchased credits never expire.
Practical details for this generator page.
On our test prompts, yes, in three specific ways: a six-constraint brief landed in one pass, six multi-word labels came back spelled correctly, and a background swap held the subject and the crop. OpenAI also puts latency up to 50% lower. None of that makes the older model unusable.
No. Both share one credit table on GPT-IMG. A 1K Standard draft is 10 credits on either, a 4K High render is 120, and reference edits run from 15 to 130. Because the price is identical, the decision is purely about output.
GPT Image 2.5 arrived September 8, 2026, five months after GPT Image 2, and targets instruction following, edit containment, iteration speed, and reference consistency rather than a new visual style. OpenAI frames it as an update, not a generational leap, which matches what we saw.
Two. If you have already shipped a catalogue rendered on it, matching that look can matter more than raw quality. And when a brief keeps failing, running it on a different model is a faster diagnostic than another prompt rewrite.
GPT Image 2.5. The six-label infographic test is the clearest case: all six labels and six self-written captions came back correct. In-image text is still the most breakable part of any image model, so read every word before shipping either way.
Yes. A new account starts with 30 free credits, which covers a 1K Standard draft on each model with credits to spare. Images made on free credits are watermarked.
Use the prompt panel above with the same account, credits, and history workflow.
